{"id":5064,"date":"2023-09-05T05:37:23","date_gmt":"2023-09-05T05:37:23","guid":{"rendered":"https:\/\/dailyai.com\/?p=5064"},"modified":"2023-09-05T05:37:23","modified_gmt":"2023-09-05T05:37:23","slug":"predicting-self-harm-and-suicide-in-adolescents-using-ml","status":"publish","type":"post","link":"https:\/\/dailyai.com\/de\/2023\/09\/predicting-self-harm-and-suicide-in-adolescents-using-ml\/","title":{"rendered":"Vorhersage von Selbstverletzungen und Selbstmord bei Jugendlichen mit ML"},"content":{"rendered":"<p><strong>Forscher der School of Clinical Medicine an der University of New South Wales haben mithilfe des maschinellen Lernens (ML) genauere Vorhersagen \u00fcber Selbstverletzungen und Selbstmord bei Jugendlichen entwickelt.<\/strong><\/p>\n<p>Die psychische Gesundheit von Jugendlichen hat sich weltweit verschlechtert, und die australischen Statistiken spiegeln die Situation in vielen anderen Gesellschaften wider. Selbstmord ist die h\u00e4ufigste Todesursache bei Australiern im Alter zwischen 15 und 24 Jahren.<\/p>\n<p>Bisherige Pr\u00e4diktoren wie fr\u00fchere Selbstverletzungen oder Selbstmordversuche haben sich als nur geringf\u00fcgig effektiver erwiesen als das Verlassen auf den Zufall. Das neue Prognosemodell der <a href=\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0165178123003967?via%3Dihub\">Forscher entwickelten mit ML<\/a> ist wesentlich effektiver.<\/p>\n<p>Der Datensatz umfasste R\u00fcckmeldungen aus Frageb\u00f6gen und Interviews mit 2.809 jugendlichen Teilnehmern der Longitudinal Study of Australian Children.<\/p>\n<p>Von den Teilnehmern gaben 5,2% an, in den letzten 12 Monaten mindestens einen Selbstmordversuch unternommen zu haben, und 10,5% berichteten von Selbstverletzungen.<\/p>\n<p>Durch den Einsatz von maschinellem Lernen zur Analyse der Daten fanden die Forscher Schl\u00fcsselpr\u00e4diktoren, die genauer waren als die bisher von Psychiatrie-Erfahrenen verwendeten.<\/p>\n<p>Die Leistung des ML-Modells wurde mit der Metrik Area Under the Curve (AUC) gemessen. Dabei handelt es sich um einen Wert zwischen 0,5 und 1, wobei 0,5 so gut wie ein M\u00fcnzwurf ist und 1 eine 100% genaue Vorhersage bedeutet.<\/p>\n<p>Die alleinige Ber\u00fccksichtigung von Selbstverletzungen und Suizidversuchen in der Vorgeschichte ergab eine AUC zwischen 0,63 und 0,647. Dies war nur geringf\u00fcgig besser als das Raten und lag unter dem f\u00fcr die Risikovorhersage akzeptablen Bereich von 0,7 bis 0,8.<\/p>\n<p>Die Pr\u00e4diktoren des ML-Modells erreichten einen AUC zwischen 0,722 und 0,74, was deutlich besser ist.<\/p>\n<p>Das Modell \u00fcberraschte die Forscher, da es zeigte, dass fr\u00fchere Selbstverletzungen oder Selbstmordversuche kein Hochrisikofaktor waren und dass das Umfeld und die elterliche Unterst\u00fctzung eine wichtigere Rolle spielten.<\/p>\n<p>Dr. Lin, einer der Forscher, sagte: \"Wir haben festgestellt, dass das Umfeld des jungen Menschen eine gr\u00f6\u00dfere Rolle spielt, als wir dachten. Aus Sicht der Pr\u00e4vention ist das eine gute Sache, denn wir wissen jetzt, dass wir mehr f\u00fcr diese Menschen tun k\u00f6nnen.<\/p>\n<p>Diese Anwendung von KI in der psychiatrischen Versorgung wird Klinikern helfen, gef\u00e4hrdete Jugendliche genauer zu beurteilen und fr\u00fcher einzugreifen.<\/p>\n<p>Dr. Lin sagte: \"Auf der Grundlage der Patientendaten k\u00f6nnte der ML-Algorithmus einen Score f\u00fcr jede Person berechnen, der in das elektronische Krankenaktensystem integriert werden k\u00f6nnte. Der Arzt k\u00f6nnte diese Informationen schnell abrufen, um seine Einsch\u00e4tzung zu best\u00e4tigen oder zu korrigieren\".<\/p>\n<p>Das Modell ist noch nicht praxisreif, aber die vielversprechenden Ergebnisse deuten darauf hin, dass es sich lohnt, diesen Weg weiterzuverfolgen.<\/p>\n<p>In den Krankenakten befinden sich viele Daten, und der Einsatz von KI zu deren Analyse wird zweifelsohne zu weiteren \u00dcberraschungen f\u00fcr die \u00c4rzte f\u00fchren.<\/p>","protected":false},"excerpt":{"rendered":"<p>Forscher der School of Clinical Medicine an der University of New South Wales haben mithilfe des maschinellen Lernens (ML) genauere Vorhersagen \u00fcber Selbstverletzungen und Selbstmord bei Jugendlichen entwickelt. Die psychische Gesundheit von Jugendlichen hat sich weltweit verschlechtert, und die australischen Statistiken spiegeln die Situation in vielen anderen Gesellschaften angemessen wider. Selbstmord ist die h\u00e4ufigste Todesursache bei Australiern im Alter zwischen 15 und 24 Jahren. Bisherige Pr\u00e4diktoren wie fr\u00fchere Selbstverletzungen oder Selbstmordversuche haben sich als nur geringf\u00fcgig effektiver erwiesen als das Verlassen auf den Zufall. Das neue Vorhersagemodell, das die Forscher mithilfe von ML entwickelt haben, ist wesentlich effektiver. Die Website<\/p>","protected":false},"author":6,"featured_media":5092,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[88],"tags":[150,204,105],"class_list":["post-5064","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ethics","tag-ai-benefits","tag-healthcare","tag-machine-learning"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Predicting self-harm and suicide in adolescents using ML | DailyAI<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/dailyai.com\/de\/2023\/09\/predicting-self-harm-and-suicide-in-adolescents-using-ml\/\" \/>\n<meta property=\"og:locale\" content=\"de_DE\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Predicting self-harm and suicide in adolescents using ML | DailyAI\" \/>\n<meta property=\"og:description\" content=\"Researchers from the School of Clinical Medicine at the University of New South Wales have used machine learning (ML) to develop more accurate predictors of self-harm and suicide in adolescents. Adolescent mental health has seen a global decline and Australian statistics are a fair reflection of those in many other societies. Suicide is the leading cause of death among Australians aged between 15 and 24. Current predictors like past self-harm or suicide attempts have been found to be only slightly more effective than relying on chance. The new predictive model the researchers developed using ML is considerably more effective. 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